3 results about "Spatial data mining" patented technology

The application discloses a kind of based on spatial data mining and geological constraint seismic activity fault model construction method, system, equipment and medium.The method is first arranged and analyzed to seismic data, extracts minimum complete subdirectory;Using improved mean shift algorithm for spatial clustering, identify each active fault corresponding small earthquake cluster;Subsequently, each fault cluster is three-dimensional slice, and least square method fitting is generated fault interpretation line;With interpretation line as foundation, initial seismic activity fault three-dimensional model is constructed, and is optimized by multi-source geological constraint, and active fault three-dimensional fine model is obtained;Finally, the model is integrated with digital earth spatial registration.This application can realize the whole process automation and quantization from seismic data analysis to active fault three-dimensional fine model construction and application, improve the objectivity, efficiency, precision and reliability of model construction, provide important technical support for seismic disaster risk assessment, active fault detection.

The application discloses a hierarchical spatial community mining method based on Gosper-island and belongs to the field of spatial data mining. First, the application carries out hierarchical partitioning of space by adopting Gosper-island, uses hierarchical partitioning coding to record the spatial hierarchical constraint of a partitioning unit, and uses Gosper space filling coding to record the spatial proximity constraint of the same hierarchical partitioning unit. Then, the hierarchical spatial network is constructed by taking the partitioning unit as a network node, the network is organized in the form of a network adjacency matrix, the network adjacency matrix heat map is drawn according to the Gosper coding sequence of the node, and finally, the hierarchical matrix block structure of the network heat map at different levels is extracted from top to bottom to obtain the hierarchical spatial community structure meeting the spatial hierarchical constraint. The application conforms to the hierarchical characteristics of the hierarchical spatial community and can effectively avoid the problems caused by the partitioning hierarchical tree.

The present application is suitable for the field of geographic information processing and spatial data mining technology, and provides a kind of geographic feature causal mining method considering topological neighborhood, comprising the following steps: obtaining the data of multiple types of geographic features in the target area, and pre-processing, obtaining the geographic feature set containing spatial position coordinates and category attributes;Based on the geographic feature set, the target area is divided into research units, and a plurality of basic research units are obtained, and based on the category attribute of the geographic feature, the spatial distribution of different category geographic features in each basic research unit is counted, and the distribution characteristic value is obtained.The quantitative identification of the causal action direction and the causal action intensity between geographic features can be realized;The structural connection between geographic features can be effectively described, the influence of pseudo correlation is reduced, and the accuracy and stability of causal relationship identification are improved.